Optimal computed tomography-based biomarkers for prediction of incisional hernia formation

PURPOSE

Unstructured data are an untapped source for surgical prediction. Modern image analysis and machine learning (ML) can harness unstructured data in medical imaging. Incisional hernia (IH) is a pervasive surgical disease, well-suited for prediction using image analysis. Our objective was to identify optimal biomarkers (OBMs) from preoperative abdominopelvic computed tomography (CT) imaging which are most predictive of IH development.

METHODS

Two hundred and twelve rigorously matched colorectal surgery patients at our institution were included. Preoperative abdominopelvic CT scans were segmented to derive linear, volumetric, intensity-based, and textural features. These features were analyzed to find a small subset of OBMs, which are maximally predictive of IH. Three ML classifiers (Ensemble Boosting, Random Forest, SVM) trained on these OBMs were used for prediction of IH.

RESULTS

Altogether, 279 features were extracted from each CT scan. The most predictive OBMs found were: (1) abdominopelvic visceral adipose tissue (VAT) volume, normalized for height; (2) abdominopelvic skeletal muscle tissue volume, normalized for height; and (3) pelvic VAT volume to pelvic outer aspect of body wall skeletal musculature (OAM) volume ratio. Among ML prediction models, Ensemble Boosting produced the best performance with an AUC of 0.85, accuracy of 0.83, sensitivity of 0.86, and specificity of 0.81.

CONCLUSION

These OBMs suggest increased intra-abdominopelvic volume/pressure as the salient pathophysiologic driver and likely mechanism for IH formation. ML models using these OBMs are highly predictive for IH development. The next generation of surgical prediction will maximize the utility of unstructured data using advanced image analysis and ML.

A Hybrid Intelligence (HI) System for Segmenting Rectoprostatic Spacer Gel and Key OARs on CT Images for Prostate Cancer Radiation Therapy Planning

PURPOSE/OBJECTIVE(S)

Our hybrid intelligence (HI) system, combining natural and artificial intelligence, is effective for auto-contouring H&N and thorax organs at risk (OARs) for radiation therapy (RT) planning with FDA 510(k) clearance. The purpose of this study is to test the HI system to segment a commercially available retroprostatic hyaluronic acid spacer gel (RSG) and pelvic OARs in planning CT images for prostate cancer RT.

HYPOTHESIS

HI can achieve clinically acceptable auto segmentation for tissue-equivalent RSG in this domain.

MATERIALS/METHODS

RSG is injected in the peri-rectal space in men with prostate cancer prior to RT to minimize rectal toxicity. 190 patients with prostate cancer were included in this post-hoc image analysis from a multi-center, prospective, randomized trial, with 136 in the spacer arm. The HI system has 3 steps: rough recognition from fuzzy model (FM) based automatic anatomy recognition (AAR-R), deep learning-based recognition (DL-R) refinement, and deep learning-based delineation (DL-D) to contour objects guided by the recognition results. FM encodes high level 3D anatomy knowledge of object shape and its relationship with other OARs; DL-R and DL-D focus on pixel-level details. The 190 studies are divided into disjoint training (100) and testing (90) subsets. 100 samples are used in DL-R and DL-D training, with 45 to build the FM for AAR-R. RSG and 4 other OARs (pelvic skin, prostate, bladder, rectum) are contoured. Location error (LE) is used to evaluate recognition; Dice coefficient (DC) and Hausdorff distance (HD) are employed to evaluate delineation. Acceptability scores (AS) (range 1-5, 1 for poor quality, 5 for best quality) from an observer study are recorded for HI-output and ground truth masks of RSG for assessing segmentation quality.

RESULTS

The HI system achieves highest DC (0.94±0.07) and lowest HD (1.96±1.61 mm) for bladder, for rectum and prostate similar DC (0.82±0.08) and HD (2.62±1.65mm), for RSG, the most challenging object, a good DC close to 0.7 (0.67±0.10) and excellent HD (2.66±1.44mm). AS for auto-segmentations (3.86±0.85) were significantly better than those for ground truth segmentations (3.45±1.00) (p = 0.02, paired t-test). Table 1 summarizes results.

CONCLUSION

The HI system achieves clinically acceptable segmentations for pelvic OARs and significantly better acceptability of segmentation of RSG compared to clinically performed ground truth segmentations. This has implications in improving efficiency and accuracy of CT-based RT planning in patients with prostate cancer.

Three-dimensional kinematic stress magnetic resonance image analysis shows promise for detecting altered anatomical relationships of tissues in the cervical spine associated with painful radiculopathy

For some patients with radiculopathy a source of nerve root compression cannot be identified despite positive electromyography (EMG) evidence. This discrepancy hampers the effective clinical management for these individuals. Although it has been well-established that tissues in the cervical spine move in a three-dimensional (3D) manner, the 3D motions of the neural elements and their relationship to the bones surrounding them are largely unknown even for asymptomatic normal subjects. We hypothesize that abnormal mechanical loading of cervical nerve roots during pain-provoking head positioning may be responsible for radicular pain in those cases in which there is no evidence of nerve root compression on conventional cervical magnetic resonance imaging (MRI) with the neck in the neutral position. This biomechanical imaging proof-of-concept study focused on quantitatively defining the architectural relationships between the neural and bony structures in the cervical spine using measurements derived from 3D MR images acquired in neutral and pain-provoking neck positions for subjects: (1) with radicular symptoms and evidence of root compression by conventional MRI and positive EMG, (2) with radicular symptoms and no evidence of root compression by MRI but positive EMG, and (3) asymptomatic age-matched controls. Function and pain scores were measured, along with neck range of motion, for all subjects. MR imaging was performed in both a neutral position and a pain-provoking position. Anatomical architectural data derived from analysis of the 3D MR images were compared between symptomatic and asymptomatic groups, and the symptomatic groups with and without imaging evidence of root compression. Several differences in the architectural relationships between the bone and neural tissues were identified between the asymptomatic and symptomatic groups. In addition, changes in architectural relationships were also detected between the symptomatic groups with and without imaging evidence of nerve root compression. As demonstrated in the data and a case study the 3D stress MR imaging approach provides utility to identify biomechanical relationships between hard and soft tissues that are otherwise undetected by standard clinical imaging methods. This technique offers a promising approach to detect the source of radiculopathy to inform clinical management for this pathology.

Relation of vision to global and regional brain MRI in multiple sclerosis

OBJECTIVE

To examine the relation between low-contrast letter acuity, an emerging visual outcome for multiple sclerosis (MS) clinical trials, and brain MRI abnormalities in an MS cohort.

METHODS

T2 lesion volume and brain parenchymal fraction were determined for whole brain and within visual pathway regions of interest. Magnetization transfer ratio histograms were examined. Vision testing was performed binocularly using low-contrast letter acuity (2.5%, 1.25% contrast) and high-contrast visual acuity (VA). Linear regression, accounting for age and disease duration, was used to assess the relation between vision and MRI measures.

RESULTS

Patients (n = 45) were aged 44 +/- 11 years, with disease duration of 5 years (range <1 to 21), Expanded Disability Status Scale score of 2.0 (0 to 6.0), and binocular Snellen acuity of 20/16 (20/12.5 to 20/25). The average T2 lesion volume was 18.5 mm(3). Patients with lower (worse) low-contrast letter acuity and high-contrast VA scores had greater T2 lesion volumes in whole brain (2.5% contrast: p = 0.004; 1.25%: p = 0.002; VA: p = 0.04), Area 17 white matter (2.5%: p < 0.001; 1.25%: p = 0.02; VA: p = 0.01), and optic radiations (2.5%: p = 0.001; 1.25%: p = 0.02; VA: p = 0.007). Within whole brain, a 3-mm(3) increase in lesion volume corresponded, on average, to a 1-line worsening of low-contrast acuity, whereas 1-line worsening of high-contrast acuity corresponded to a 5.5-mm(3) increase.

CONCLUSIONS

Low-contrast letter acuity scores correlate well with brain MRI lesion burden in multiple sclerosis (MS), supporting validity for this vision test as a candidate for clinical trials. Disease in the postgeniculate white matter is a likely contributor to visual dysfunction in MS that may be independent of acute optic neuritis history.

Cartilage anlagen adapt in response to static deformation

Connective tissue adaptation, including the development of cartilaginous anlagen into bones, is widely believed to be related to dynamic, intermittent load and stress histories. Static stresses, on the other hand, are generally believed deleterious in tissue adaptation. Using serial MRI in a natural human experiment (manipulation and corrective casting of infant clubfoot), we have observed casting produces two effects: (1) the well recognized change in relative positions of the hindfoot anlagen; (2) a newly recognized immediate shape change in the anlagen. These changes seemingly enhance the rate of growth of the anlagen and of the ossific nucleus. The shape change or deformation in the anlagen would occur as a result of alterations in the magnitudes and directions of loading from soft tissue attachments and muscle activity and would necessarily be associated with changes in the stress states within the anlagen and, when present, the ossific nuclei. Given the known role of load and stress history in tissue adaptation, we presume the reduced stress histories influence the enhanced growth rates. These observations contradict some current theories of tissue adaptation since static, rather than dynamic stresses play a crucial role in accelerating the growth and development of anlagen in the infant clubfoot.

The effect of ankle ligament damage and surgical reconstructions on the mechanics of the ankle and subtalar joints revealed by three-dimensional stress MRI

Common image-based diagnostic techniques used to detect ankle ligament injuries or the effects of those injuries (e.g., mechanical instability) include magnetic resonance imaging (MRI) and stress radiography. Each of these techniques has limitations. The interpretation of the results obtained through stress radiography, a two-dimensional technique, is highly controversial. MRI can facilitate visualization of soft tissue, but three-dimensional visualization of the full length of the ligaments or detecting partial ligament damage is difficult. This work is part of a long-term study aimed at improving the diagnostic ability of MRI by utilizing it not only to visualize the ligaments but also to detect the mechanical instability produced at the ankle and subtalar joints due to ligament damage. The goal of the present study was to evaluate the ability of a previously developed technique called 3D stress MRI (sMRI) to detect in vitro the effect of damage to the lateral collateral ligaments and the stabilizing effect produced by two common surgical reconstruction techniques. MRI data were collected from eight cadaver limbs in a MR compatible ankle-loading device in neutral, inversion, and anterior drawer. Each specimen was tested intact, after cutting the anterior talo-fibular ligament followed by the calcaneo-fibular ligament and after applying two reconstructions. Ligament injuries produced significant changes in the response of the ankle and subtalar joints to load as detected by the 3D stress MRI technique. Both surgical procedures restored mechanical stability to the joints but they differed in the amount and type of stabilization achieved. We concluded that 3D sMRI can extend the diagnostic power of MRI from the current practice of slice-by-slice visualization to the assessment of mechanical function, the compromise in this function due to injury, and the effects of surgery.

Mechanics of the ankle and subtalar joints revealed through a 3D quasi-static stress MRI technique

A technique to study the three-dimensional (3D) mechanical characteristics of the ankle and of the subtalar joints in vivo and in vitro is described. The technique uses an MR scanner compatible 3D positioning and loading linkage to load the hindfoot with precise loads while the foot is being scanned. 3D image processing algorithms are used to derive from the acquired MR images bone morphology, hindfoot architecture, and joint kinematics. The technique was employed to study these properties both in vitro and in vivo. The ankle and subtler joint motion and the changes in architecture produced in response to an inversion load and an anterior drawer load were evaluated. The technique was shown to provide reliable measures of bone morphology. The left-to-right variations in bone morphology were less than 5%. The left-to-right variations in unloaded hindfoot architecture parameters were less than 10%, and these properties were only slightly affected by inversion and anterior drawer loads. Inversion and anterior drawer loads produced motion both at the ankle and at the subtalar joint. In addition, high degree of coupling, primarily of internal rotation with inversion, was observed both at the ankle and at the subtalar joint. The in vitro motion produced in response to inversion and anterior drawer load was greater than the in vivo motion. Finally, external motion, measured directly across the ankle complex, produced in response to load was much greater than the bone movements measured through the 3D stress MRI technique indicating the significant effect of soft tissue and skin interference.

A sensor array processing approach to object region detection

This paper presents a new approach for medical image analysis. It translates the object region-detection problem into a sensor array processing framework and detects the number of object regions based on the signal eigenstructure of the converted array system. The theoretical and experimental results obtained by using this approach on various medical images were in good agreement.

Multiprotocol MR image segmentation in multiple sclerosis: experience with over 1,000 studies

RATIONALE AND OBJECTIVES

Multiple sclerosis (MS) is an acquired disease of the central nervous system. Several clinical measures are commonly used to express the severity of the disease, including the Expanded Disability Status Scale and the ambulation index. These measures are subjective and may be difficult to reproduce. The aim of this research is to investigate the possibility of developing more objective measures derived from MR imaging.

MATERIALS AND METHODS

Various magnetic resonance (MR) imaging protocols are being investigated for the study of MS. Seeking to replace the Expanded Disability Status Scale and ambulation index with an objective means to assess the natural course of the disease and its response to therapy, the authors have developed multiprotocol MR image segmentation methods based on fuzzy connectedness to quantify both macrosopic features of the disease (lesions, gray matter, white matter, cerebrospinal fluid, and brain parenchyma) and the microscopic appearance of diseased white matter. Over 1,000 studies have been processed to date.

RESULTS

By far the strongest correlations with the clinical measures were demonstrated by the magnetization transfer ratio histogram parameters obtained for the various segmented tissue regions. These findings emphasize the importance of considering the microscopic and diffuse nature of the disease in the individual tissue regions. Brain parenchymal volume also demonstrated a strong correlation with clinical measures, which suggests that brain atrophy is an important disease indicator.

CONCLUSION

Fuzzy connectedness is a viable, highly reproducible segmentation method for studying MS.

Scale-based diffusive image filtering preserving boundary sharpness and fine structures

Image acquisition techniques often suffer from low signal-to-noise ratio (SNR) and/or contrast-to-noise ratio (CNR). Although many acquisition techniques are available to minimize these, post acquisition filtering is a major off-line image processing technique commonly used to improve the SNR and CNR. A major drawback of filtering is that it often diffuses/blurs important structures along with noise. In this paper, we introduce two scale-based filtering methods that use local structure size or "object scale" information to arrest smoothing around fine structures and across even low-gradient boundaries. The first of these methods uses a weighted average over a scale-dependent neighborhood while the other employs scale-dependent diffusion conductance to perform filtering. Both methods adaptively modify the degree of filtering at any image location depending on local object scale. Object scale allows us to accurately use a restricted homogeneity parameter for filtering in regions with fine details and in the vicinity of boundaries while a generous parameter in the interiors of homogeneous regions. Qualitative experiments based on both phantoms and patient magnetic resonance images show significant improvements using the scale-based methods over the extant anisotropic diffusive filtering method in preserving fine details and sharpness of object boundaries. Quantitative analyses utilizing 25 phantom images generated under a range of conditions of blurring, noise, and background variation confirm the superiority of the new scale-based approaches.

Brain atrophy in relapsing-remitting multiple sclerosis: fractional volumetric analysis of gray matter and white matter

PURPOSE

To determine the fractional brain tissue volume changes in the gray matter and white matter of patients with relapsing-remitting multiple sclerosis (MS) and to correlate these measurements with clinical disability and total lesion load.

MATERIALS AND METHODS

Thirty patients with relapsing-remitting MS and 25 healthy control subjects underwent magnetic resonance imaging. Fractional brain tissue volumes (tissue volume relative to total intracranial volume) were obtained from the total segmented gray matter and white matter in each group and were analyzed.

RESULTS

The fractional volume of white matter versus that of gray matter was significantly lower (-6.4%) in patients with MS (P <.0001) than in control subjects. Neither gray matter nor white matter fractional volume measurements correlated with clinical disability in the patients with MS.

CONCLUSION

Loss of brain parenchymal volume in patients with relapsing-remitting MS is predominantly confined to white matter. Analysis of fractional brain tissue volumes provides additional information useful in characterizing MS and may have potential in evaluating treatment strategies.

Breast tissue density quantification via digitized mammograms

Studies reported in the literature indicate that breast cancer risk is associated with mammographic densities. An objective, repeatable, and a quantitative measure of risk derived from mammographic densities will be of considerable use in recommending alternative screening paradigms and/or preventive measures. However, image processing efforts toward this goal seem to be sparse in the literature, and automatic and efficient methods do not seem to exist. In this paper, we describe and validate an automatic and reproducible method to segment dense tissue regions from fat within breasts from digitized mammograms using scale-based fuzzy connectivity methods. Different measures for characterizing mammographic density are computed from the segmented regions and their robustness in terms of their linear correlation across two different projections--cranio-caudal and medio-lateral-oblique--are studied. The accuracy of the method is studied by computing the area of mismatch of segmented dense regions using the proposed method and using manual outlining. A comparison between the mammographic density parameter taking into account the original intensities and that just considering the segmented area indicates that the former may have some advantages over the latter.

Artery-vein separation via MRA--an image processing approach

This paper presents a near-automatic process for separating vessels from background and other clutter as well as for separating arteries and veins in contrast-enhanced magnetic resonance angiographic (CE-MRA) image data, and an optimal method for three-dimensional visualization of vascular structures. The separation process utilizes fuzzy connected object delineation principles and algorithms. The first step of this separation process is the segmentation of the entire vessel structure from the background and other clutter via absolute fuzzy connectedness. The second step is to separate artery from vein within this entire vessel structure via iterative relative fuzzy connectedness. After seed voxels are specified inside artery and vein in the CE-MRA image, the small regions of the bigger aspects of artery and vein are separated in the initial iterations, and further detailed aspects of artery and vein are included in later iterations. At each iteration, the artery and vein compete among themselves to grab membership of each voxel in the vessel structure based on the relative strength of connectedness of the voxel in the artery and vein. This approach has been implemented in a software package for routine use in a clinical setting and tested on 133 CE-MRA studies of the pelvic region and two studies of the carotid system from six different hospitals. In all studies, unified parameter settings produced correct artery-vein separation. When compared with manual segmentation/separation, our algorithms were able to separate higher order branches, and therefore produced vastly more details in the segmented vascular structure. The total operator and computer time taken per study is on the average about 4.5 min. To date, this technique seems to be the only image processing approach that can be routinely applied for artery and vein separation.

Magnetization transfer ratio histogram analysis of gray matter in relapsing-remitting multiple sclerosis

BACKGROUND AND PURPOSE

Gray matter may be affected by multiple sclerosis (MS), a white matter disease. Magnetization transfer ratio (MTR) is a sensitive and quantitative marker for structural abnormalities, and has been used frequently in the imaging of MS. In this study, we evaluated the amount of MTR of gray matter among patients with relapsing-remitting MS and healthy control subjects as well as the correlation between gray matter MTR abnormality and neurologic disability associated with relapsing-remitting MS.

METHODS

We obtained fast spin-echo dual-echo and magnetization transfer (with and without MT saturation pulses) images from eighteen patients with relapsing-remitting MS and 18 age-matched healthy control subjects. Gray matter was segmented using a semiautomated system. Gray matter MTR histogram parameters, Kurtzke Expanded Disability Status Scale (EDSS), total T2 lesion volume, and gray matter volumes were obtained for statistical analysis.

RESULTS

A significant difference was found in gray matter MTR between patients with relapsing-remitting MS and healthy subjects (mean and median). Gray matter MTR histogram normalized peak heights in patients inversely correlated with EDSS (r = -0.65, P =.01). There was also an inverse correlation between mean MTR of gray matter and total T2 lesion volume.

CONCLUSION

The MTR of gray matter significantly differed between patients with relapsing-remitting MS and healthy control subjects, suggesting that MS is a more diffuse disease affecting the whole brain, and neuronal damage accumulates in step with T2 lesion volume. Our finding of the relationship between gray matter MTR and EDSS indicates that measurement of gray matter abnormality may be a potentially useful tool for assessing clinical disability in MS.

An in vivo analysis of the motion of the peri-talar joint complex based on MR imaging

The purpose of this work is to characterize the three-dimensional (3-D) motion of the peritalar joint complex in vivo using magnetic resonance imaging (MRI). Each image data set utilized in this study is made of 60 longitudinal MR slices of the foot in each of eight positions from extreme pronation to extreme supination. We acquired and analyzed ten such data sets from normal subjects, seven data sets from pathological joints and two postoperative data sets. We segmented and formed the surfaces of the calcaneus, talus, cuboid and navicular from all data sets. About 30 geometrical parameters are computed for each joint in each position. The results present features of normal motion and show how normal and abnormal motion can be distinguished. They also show the consequences of surgery on the motion. This non- invasive method offers a unique tool to characterize and quantify the 3-D motion of the rearfoot in vivo from MR images.

A 3D generalization of user-steered live-wire segmentation

We have been developing user-steered image segmentation methods for situations which require considerable human assistance in object definition. In the past, we have presented two paradigms, referred to as live-wire and live-lane, for segmenting 2D/3D/4D object boundaries in a slice-by-slice fashion, and demonstrated that live-wire and live-lane are more repeatable, with a statistical significance level of P < 0.03, and are 1.5-2.5 times faster, with a statistical significance level of P < 0.02, than manual tracing. In this paper, we introduce a 3D generalization of the live-wire approach for segmenting 3D/4D object boundaries which further reduces the time spent by the user in segmentation. In a 2D live-wire, given a slice, for two specified points (pixel vertices) on the boundary of the object, the best boundary segment is the minimum-cost path between the two points, described as a set of oriented pixel edges. This segment is found via Dijkstra's algorithm as the user anchors the first point and moves the cursor to indicate the second point. A complete 2D boundary is identified as a set of consecutive boundary segments forming a "closed", "connected", "oriented" contour. The strategy of the 3D extension is that, first, users specify contours via live-wiring on a few slices that are orthogonal to the natural slices of the original scene. If these slices are selected strategically, then we have a sufficient number of points on the 3D boundary of the object to subsequently trace optimum boundary segments automatically in all natural slices of the 3D scene. A 3D object boundary may define multiple 2D boundaries per slice. The points on each 2D boundary form an ordered set such that when the best boundary segment is computed between each pair of consecutive points, a closed, connected, oriented boundary results. The ordered set of points on each 2D boundary is found from the way the users select the orthogonal slices. Based on several validation studies involving segmentation of the bones of the foot in MR images, we found that the 3D extension of live-wire is more repeatable, with a statistical significance level of P < 0.0001, and 2-6 times faster, with a statistical significance level of P < 0.01, than the 2D live-wire method, and 3-15 times faster than manual tracing.

MR image analysis in multiple sclerosis

MR imaging is the ubiquitous imaging modality used for studying multiple sclerosis (MS). A variety of MR imaging protocols, including T2, spin density, T1-weighted, with and without gadolinium, and magnetization transfer imaging, have been used in studying MS. This article provides an overview of the techniques recently developed for quantifying the extent of MS through the application of MR imaging.

Numerical tissue characterization in MS via standardization of the MR image intensity scale

Image intensity standardization is a recently developed postprocessing method that is capable of correcting the signal intensity variations in MR images. We evaluated signal intensity of healthy and diseased tissues in 10 multiple sclerosis (MS) patients based on standardized dual fast spin-echo MR images using a numerical postprocessing technique. The main idea of this technique is to deform the volume image histogram of each study to match a standard histogram and to utilize the resulting transformation to map the image intensities into standard scale. Upon standardization, the coefficients of variation of signal intensities for each segmented tissue (gray matter, white matter, lesion plaques, and diffuse abnormal white matter) in all patients were significantly smaller (2.3-9.2 times) than in the original images, and the same tissues from different patients looked alike, with similar intensity characteristics. Numerical tissue characterizability of different tissues in MS achieved by standardization offers a fixed tissue-specific meaning for the numerical values and can significantly facilitate image segmentation and analysis.

Multiple sclerosis: magnetization transfer histogram analysis of segmented normal-appearing white matter

PURPOSE

To investigate and characterize the global distribution of magnetization transfer (MT) ratio values of normal-appearing white matter (NAWM) in patients with relapsing-remitting multiple sclerosis (MS) and test the hypothesis that the MT histogram for NAWM reflects disease progression.

MATERIALS AND METHODS

Conventional and MT magnetic resonance (MR) images were obtained in 23 patients and 25 healthy volunteers. Clinical tests for comparison with the MT histogram parameters included the Extended Disability Status Scale and the ambulation index. Lesion load calculated with T2-weighted MR images and whole-brain and white matter volumes were measured.

RESULTS

The location of the MT histogram peak and the mean MT ratio for NAWM were significantly lower in patients with MS than in control subjects. In longitudinal studies, the histogram peak location and mean MT ratio shifted in the direction of normal values as the duration of disease increased. A mean of 26.5% of the volume of new lesions identified on the later studies were demonstrated to have originated in NAWM corresponding to "lost" pixels on the histogram.

CONCLUSION

MT histogram analysis of NAWM, including longitudinal analysis, may provide new prognostic information regarding lesion formation and increase understanding of the course of the disease.

The effect of gadolinium-enhancing lesions on whole brain atrophy in relapsing-remitting MS

OBJECTIVE

To determine the relationship between gadolinium-enhancing lesions and changes in whole brain parenchymal volume in patients with relapsing-remitting MS, and to test the hypothesis that gadolinium enhancement is a predictor of whole brain atrophy.

METHODS

Twenty-four patients with clinically definite MS were imaged over 2 years. A computer-assisted segmentation technique based on high-resolution MRI was used to quantify gadolinium-enhancing T1 lesion volume and brain parenchyma and CSF volumes. Percent brain parenchymal volume (PBV) relative to the total intracranial volume was calculated, and changes in PBV were used to represent the degree of whole brain atrophy over 2 years.

RESULTS

PBV at baseline was dependent on duration of MS, and a significant decrease in PBV was observed over the course of the study. Changes in enhanced T1 lesion load failed to correlate with changes in PBV, and multiple regression analyses determined that enhanced T1 lesion load at baseline was not a significant predictor of subsequent change in PBV.

CONCLUSIONS

MR visible inflammation as demonstrated by enhanced T1 lesions is not a significant factor in the pathogenesis of whole brain atrophy in relapsing-remitting MS, suggesting that a more global pathologic process is responsible for the loss of brain parenchymal volume.

Magnetization transfer histogram analysis of monosymptomatic episodes of neurologic dysfunction: preliminary findings

BACKGROUND AND PURPOSE

Patients presenting with a monosymptomatic episode of neurologic dysfunction (MEND) have a high probability of developing multiple sclerosis (MS). Our study was designed to determine whether magnetization transfer (MT) histogram analysis could predict the development of MS for a cohort of patients presenting with a MEND.

METHODS

Eleven patients with a MEND and 21 age-matched control volunteers underwent MR imaging. Six patients underwent serial MR examinations. MT ratio histogram peak height (MTRHPH) and the location of the MT ratio histogram peak (LOC MTRHP) were determined for patients and control volunteers. T2 lesion volume was also calculated. Patients were clinically followed up for 587 +/- 308 days to determine or rule out the development of MS.

RESULTS

Three patients went on to develop MS. There was no statistically significant difference in the MTRHPH (P = .65) and the LOC MTRHP (P = .71) between patients and control volunteers. For those patients who underwent multiple examinations, no statistically significant differences in the MTRHPH (P = .64), LOC MTRHP (P =.58), and T2 lesion volume (P = .47) were seen. There were no statistically significant correlations between any of the parameters studied.

CONCLUSION

We found no difference in MT histogram parameters among control volunteers, patients with a MEND without MS, and patients with a MEND who went on to a diagnosis of MS. Our preliminary findings suggest that there may not be a substrate of disease in the normal-appearing white matter that is predictive of the development of MS.

Brain atrophy in relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis: longitudinal quantitative analysis

PURPOSE

To determine annual rates of volumetric changes in the whole-brain parenchyma of patients with relapsing-remitting and secondary progressive multiple sclerosis (MS) and test the hypothesis that these changes correlate with clinical disability.

MATERIALS AND METHODS

A computer-assisted segmentation technique with thin-section magnetic resonance (MR) imaging was used in 36 patients with MS (27 relapsing-remitting, nine secondary progressive) and in 20 control subjects to quantify brain and cerebrospinal fluid volumes. To determine the degree of brain atrophy, the percentage brain parenchyma volume (PBV) relative to that of intracranial contents was calculated.

RESULTS

At the beginning of the study, the PBV was smaller in the MS group than in the control group (P = .007); brain parenchyma volumes were similar. The median rate of brain volume loss was 17.3 mL per year in patients with relapsing-remitting MS and 23.6 mL per year in those with secondary progressive MS. There was a negative correlation between brain atrophy and Expanded Disability Status Scale (EDSS) score in patients with secondary progressive MS (r = -0.69, P = .004) and no correlation in patients with relapsing-remitting MS. T2 lesion volume did not correlate with brain atrophy in either group.

CONCLUSION

The correlation between brain atrophy and EDSS score was better in patients with secondary progressive MS than in those with relapsing-remitting MS.

Glatiramer acetate (Copaxone) treatment in relapsing-remitting MS: quantitative MR assessment

OBJECTIVE

To evaluate the efficacy of glatiramer acetate (GA, Copaxone; Teva Pharmaceutical Industries, Ltd., Petah Tiqva, Israel) by MRI-based measures in patients with relapsing-remitting (RR) MS.

METHODS

Twenty-seven patients with clinically definite RR-MS were treated with either 20 mg of GA by daily subcutaneous self-injection (n = 14) or placebo (n = 13) for approximately 24 months. Axial dual-echo fast-spin-echo T2-weighted images and T1-weighted images before and after gadolinium (Gd) were acquired at 1.5 tesla and transferred into an image processing computer system. The main outcome measures were the number of Gd-enhanced T1 and T2 lesions and their volume as well as brain parenchyma volume.

RESULTS

The values of age, disease duration, Expanded Disability Status Scale (EDSS) score, the number of T1- and T2-weighted lesions, and their volume were similar between GA- and placebo-receiving groups at the entry of this study. There was a decrease in the number of T1-enhanced lesions (p = 0.03) and a significant percent annual decrease of their volume in GA recipients compared with those of placebo recipients. There were no significant differences between changes in the two groups in the number of T2 lesions and their volume. The loss of brain tissue was significantly smaller in the GA group compared with that of the placebo group.

CONCLUSIONS

These results show that GA treatment may decrease both lesion inflammation and the rate of brain atrophy in RR-MS.

New variants of a method of MRI scale standardization

One of the major drawbacks of magnetic resonance imaging (MRI) has been the lack of a standard and quantifiable interpretation of image intensities. Unlike in other modalities, such as X-ray computerized tomography, MR images taken for the same patient on the same scanner at different times may appear different from each other due to a variety of scanner-dependent variations and, therefore, the absolute intensity values do not have a fixed meaning. We have devised a two-step method wherein all images (independent of patients and the specific brand of the MR scanner used) can be transformed in such a way that for the same protocol and body region, in the transformed images similar intensities will have similar tissue meaning. Standardized images can be displayed with fixed windows without the need of per-case adjustment. More importantly, extraction of quantitative information about healthy organs or about abnormalities can be considerably simplified. This paper introduces and compares new variants of this standardizing method that can help to overcome some of the problems with the original method.

An ultra-fast user-steered image segmentation paradigm: live wire on the fly

We have been developing general user steered image segmentation strategies for routine use in applications involving a large number of data sets. In the past, we have presented three segmentation paradigms: live wire, live lane, and a three-dimensional (3-D) extension of the live-wire method. In this paper, we introduce an ultra-fast live-wire method, referred to as live wire on the fly, for further reducing user's time compared to the basic live-wire method. In live wire, 3-D/four-dimensional (4-D) object boundaries are segmented in a slice-by-slice fashion. To segment a two-dimensional (2-D) boundary, the user initially picks a point on the boundary and all possible minimum-cost paths from this point to all other points in the image are computed via Dijkstra's algorithm. Subsequently, a live wire is displayed in real time from the initial point to any subsequent position taken by the cursor. If the cursor is close to the desired boundary, the live wire snaps on to the boundary. The cursor is then deposited and a new live-wire segment is found next. The entire 2-D boundary is specified via a set of live-wire segments in this fashion. A drawback of this method is that the speed of optimal path computation depends on image size. On modestly powered computers, for images of even modest size, some sluggishness appears in user interaction, which reduces the overall segmentation efficiency. In this work, we solve this problem by exploiting some known properties of graphs to avoid unnecessary minimum-cost path computation during segmentation. In live wire on the fly, when the user selects a point on the boundary the live-wire segment is computed and displayed in real time from the selected point to any subsequent position of the cursor in the image, even for large images and even on low-powered computers. Based on 492 tracing experiments from an actual medical application, we demonstrate that live wire on the fly is 1.3-31 times faster than live wire for actual segmentation for varying image sizes, although the pure computational part alone is found to be about 120 times faster.

On standardizing the MR image intensity scale

The lack of a standard image intensity scale in MRI causes many difficulties in image display and analysis. A two-step postprocessing method is proposed for standardizing the intensity scale in such a way that for the same MR protocol and body region, similar intensities will have similar tissue meaning. In the first step, the parameters of the standardizing transformation are "learned" from a set of images. In the second step, for each MR study these parameters are used to map their histogram into the standardized histogram. The method was tested quantitatively on 90 whole-brain studies of multiple sclerosis patients for several protocols and qualitatively for several other protocols and body regions. Measurements using mean squared difference showed that the standardized image intensities have statistically significantly (P < 0.01) more consistent range and meaning than the originals. Fixed gray level windows can be established for the standardized images and used for display without the need of per case adjustment. Preliminary results also indicate that the method facilitates improving the degree of automation of image segmentation. Magn Reson Med 42:1072-1081, 1999.

On standardizing the MR image intensity scale

The lack of a standard image intensity scale in MRI causes many difficulties in image display and analysis. A two-step postprocessing method is proposed for standardizing the intensity scale in such a way that for the same MR protocol and body region, similar intensities will have similar tissue meaning. In the first step, the parameters of the standardizing transformation are "learned" from a set of images. In the second step, for each MR study these parameters are used to map their histogram into the standardized histogram. The method was tested quantitatively on 90 whole-brain studies of multiple sclerosis patients for several protocols and qualitatively for several other protocols and body regions. Measurements using mean squared difference showed that the standardized image intensities have statistically significantly (P < 0.01) more consistent range and meaning than the originals. Fixed gray level windows can be established for the standardized images and used for display without the need of per case adjustment. Preliminary results also indicate that the method facilitates improving the degree of automation of image segmentation. Magn Reson Med 42:1072-1081, 1999.

Relapsing-remitting multiple sclerosis: longitudinal analysis of MR images--lack of correlation between changes in T2 lesion volume and clinical findings

PURPOSE

To determine the relationship between T2 lesion volume and either disability measurements or change in T2 lesion volume over time in multiple sclerosis (MS).

MATERIALS AND METHODS

Eighteen patients (age range, 26-53 years) with clinically proved relapsing-remitting MS were examined every 6 months for over 2 years. Three-millimeter-thick contiguous images of the whole brain were obtained. T2 lesion volume was calculated with a highly reproducible volumetric computer method.

RESULTS

A substantial annual increase in T2 lesion volume, with a median annual increase of approximately 8%, was demonstrated. However, there was no significant correlation between absolute T2 lesion volume and either the absolute expanded disability status scale (EDSS) grade (P = .32) or the absolute ambulation index (AI) (P = .20). In addition, no significant correlation between change in T2 lesion volume and change in EDSS grade (P = .42) or AI (P = .37) was found. There was no significant correlation between T2 lesion volume and duration of disease (P = .08).

CONCLUSION

There is no significant correlation between T2 lesion volume and standardized disability measurements despite a substantial increase in T2 lesion volume over time. Patients have an increase in total T2 lesion volume in the brain regardless of their clinical status or disability measurements. T2 lesion volumes as outcomes in therapeutic clinical trials on MS should be viewed as secondary outcomes rather than as surrogate markers of clinical responses.

Serial analysis of magnetization-transfer histograms and Expanded Disability Status Scale scores in patients with relapsing-remitting multiple sclerosis

BACKGROUND AND PURPOSE

Magnetization transfer ratio histogram peak height (MTR-HPH) has been shown to correlate with macroscopic and microscopic brain disease in patients with multiple sclerosis (MS). We studied the changes in MTR-HPH and in Kurtzke's Expanded Disability Status Scale (EDSS) scores over time in a group of patients with relapsing-remitting MS.

METHODS

Twenty adult patients with relapsing-remitting MS (four men and 16 women) were followed up for a period of 334 to 1313 days. In all, 86 MR imaging studies of the brain were obtained, and MTR-HPH was calculated for each MR examination by using a semiautomated technique. Changes in MTR-HPH were compared between patients over the study's duration. A neurologist specialized in the care of MS patients assessed the EDSS score for each patient as a measure of clinical disability.

RESULTS

Serial MR data showed a subtle but significant decline in MTR-HPH with time. No significant changes in EDSS scores were noted over the same period.

CONCLUSION

Patients with relapsing-remitting MS have a significant progressive decline in normalized MTR-HPH, which is independent of EDSS score. MTR-HPH measurements can be used to monitor subclinical disease in patients with relapsing-remitting MS over a short time frame of 1 to 4 years. This parameter might be applied in future therapeutic trials to assess its usefulness.

MR imaging quantitation of gray matter involvement in multiple sclerosis and its correlation with disability measures and neurocognitive testing

BACKGROUND AND PURPOSE

Multiple sclerosis (MS) is the most common inflammatory disease of the central nervous system and manifests both physical and neurocognitive disabilities. Although predominantly a disease of the white matter, MS is also characterized by lesions in the gray matter. Previous pathologic studies have found that cortical and deep gray matter lesions comprised 5% and 4%, respectively, of total lesions. Using software for lesion detection and quantitation, our study was designed to determine MS involvement in the cortical and deep gray matter and to correlate gray matter lesion load with neurocognitive function and the Kurtzke Expanded Disability Status Scale.

METHODS

Using a semiautomated segmentation algorithm that detected and delineated all possible brain MS lesions on MR images, we investigated gray matter lesion volume in 18 patients with untreated relapsing-remitting MS. Cortical and deep gray matter lesions then were correlated with the neurocognitive and physical disability measurements.

RESULTS

We found that cortical gray matter lesions comprised approximately 5.7% of the total lesion volume, whereas deep gray matter lesions comprised another 4.6% in this patient cohort. No strong correlations were found between gray matter lesions and disability status or neurocognitive function.

CONCLUSION

These results are similar to those found in previous pathologic studies. The cortical lesion load in cases of relapsing-remitting MS, as measured by MR imaging, represents less than 6% of the total lesion volume and does not correlate with disability measures or neurocognitive tests.

A characterization of the geometric architecture of the peritalar joint complex via MRI: an aid to the classification of foot type

The purpose of this work is to study the architecture of the rearfoot using in vivo MR image data. Each data set used in this study is made of sixty sagittal slices of the foot acquired in a 1.5-T commercial GE MR system. We use the live-wire method to delineate boundaries and form the surfaces of the bones. In the first part of this work, we describe a new method to characterize the three-dimensional (3-D) relationships of four bones of the peritalar complex and apply this description technique to data sets from ten normal subjects and from seven pathological cases. In the second part, we propose a procedure to classify feet, based on the values of these new architectural parameters. We conclude that this noninvasive method offers a unique tool to characterize the 3-D architecture of the feet in live patients, based on a set of new architectural parameters. This can be integrated into a set of tools to improve diagnosis and treatment of foot malformations.

Three-dimensional visualization and analysis methodologies: a current perspective

Three-dimensional (3D) imaging was developed to provide both qualitative and quantitative information about an object or object system from images obtained with multiple modalities including digital radiography, computed tomography, magnetic resonance imaging, positron emission tomography, single photon emission computed tomography, and ultrasonography. Three-dimensional imaging operations may be classified under four basic headings: preprocessing, visualization, manipulation, and analysis. Preprocessing operations (volume of interest, filtering, interpolation, registration, segmentation) are aimed at extracting or improving the extraction of object information in given images. Visualization operations facilitate seeing and comprehending objects in their full dimensionality and may be either scene-based or object-based. Manipulation may be either rigid or deformable and allows alteration of object structures and of relationships between objects. Analysis operations, like visualization operations, may be either scene-based or object-based and deal with methods of quantifying object information. There are many challenges involving matters of precision, accuracy, and efficiency in 3D imaging. Nevertheless, 3D imaging is an exciting technology that promises to offer an expanding number and variety of applications.

Differences between relapsing-remitting and chronic progressive multiple sclerosis as determined with quantitative MR imaging

PURPOSE

To investigate the cross-sectional relationships among multiple quantitative brain magnetic resonance (MR) imaging measurements in patients with relapsing-remitting versus chronic progressive multiple sclerosis (MS).

MATERIALS AND METHODS

Thirty-eight patients with MS (relapsing-remitting, 26, chronic progressive, 12) were examined. Lesion volume on T2-weighted MR images, contrast material-enhancing lesion volume, percentage of brain parenchymal volume (brain volume/[brain volume + cerebrospinal fluid volume), and magnetization transfer ratio histogram peak height for the whole brain were calculated.

RESULTS

Significant negative correlation was noted between volume on T2-weighted images and magnetization transfer ratio histogram peak height for both the relapsing-remitting and chronic progressive groups (P < .001 for both). A positive correlation was demonstrated for lesion volume on T2-weighted images and enhancing lesion volume in the relapsing-remitting group (P < .01) but not in the chronic progressive group. Negative correlations were demonstrated for enhancing lesion volume and magnetization transfer ratio histogram peak height (P = .02), for Expanded Disability Status Scale score and magnetization transfer histogram peak height (P = .02), and for Expanded Disability Status Scale score and percentage of brain parenchymal volume in the relapsing-remitting group (P = .004) but not in the chronic progressive group.

CONCLUSION

The cross-sectional relationships among multiple quantitative brain MR imaging measurements are different between relapsing-remitting and chronic progressive MS.

3D MR image analysis of the morphology of the rear foot: application to classification of bones

The purpose of this work is to characterize the three-dimensional (3D) morphology of the bones of the rear foot using MR image data. It has two sub-aims: (i) to study the variability of the various computed architectural measures caused by the subjectivity and variations in the various processing operations; (ii) to study the morphology of the bones included in the peritalar complex. Each image data set utilized in this study consists of sixty sagittal slices of the foot acquired on a 1.5 T commercial GE MR system. The description of the rear foot morphology is based mainly on the principal axes, which represent the inertia axes of the bones, and on the bone surfaces. We use the live-wire method [Falcao AX, Udupa JK, Samarasekera S, Shoba S, Hirsch BE, Lotufo RA. User-steered image segmentation paradigms: live wire and live lane. Proceedings of the Society of Photo-optical Instrumentation Engineers 1996;2710:278-288] for segmenting and forming the surfaces of the bones. In the first part of this work, we focus on the analysis of the dependence of the principal axes system on segmentation and on scan orientation. In the second part, we describe the normal morphology of the rear foot considering the four bones namely calcaneus, cuboid, navicular, and talus, and compare this to a population from the upper Pleistocene. We conclude that this non-invasive method offers a unique tool to characterize the bone morphology in live patients towards the goal of understanding the architecture and kinematics of normal and pathological joints in vivo.

A task-specific evaluation of three-dimensional image interpolation techniques

Image interpolation is an important operation that is widely used in medical imaging, image processing, and computer graphics. A variety of interpolation methods are available in the literature. However, their systematic evaluation is lacking. In a previous paper, we presented a framework for the task-independent comparison of interpolation methods based on certain image-derived figures of merit using a variety of medical image data pertaining to different parts of the human body taken from different modalities. In this work, we present an objective task-specific framework for evaluating interpolation techniques. The task considered is how the interpolation methods influence the accuracy of quantification of the total volume of lesions in the brain of multiple sclerosis (MS) patients. Sixty lesion-detection experiments coming from ten patient studies, two subsampling techniques and the original data, and three interpolation methods are carried out, along with a statistical analysis of the results.

Analysis of in vivo 3-D internal kinematics of the joints of the foot

This paper describes a methodology for the analysis of three-dimensional (3-D) kinematics of live joints of the foot based on tomographic image data acquired via magnetic resonance (MR) imaging. A mechanical jig facilitates acquisition of MR images corresponding to different positions of the joint in a pronation-supination motion. The surfaces of the individual tarsal bones are constructed by segmenting the MR images. A mathematical description of the motion of the individual bones and of their relative motion is derived by computing the rigid transformation required to match the centroids and the principal axes of the surfaces. The mathematically described motion is animated via surface renditions of the bones. The kinematics of the bones are analyzed based on features extracted from the motion description and on how they vary with motion. Based on 17 joints that have been imaged, which includes an abnormal joint and the same joint after surgical correction, we conclude that this methodology offers a practical tool for measuring internal 3-D kinematics of joints in vivo and for characterizing and quantifying with specificity normal kinematics and their pathological deviations. Some of the 3-D kinematic animations generated using the methods of this paper for normal joints can be seen at: http:(/)/www.mipg.upenn.edu.

An objective comparison of 3-D image interpolation methods

To aid in the display, manipulation, and analysis of biomedical image data, they usually need to he converted to data of isotropic discretization through the process of interpolation. Traditional techniques consist of direct interpolation of the grey values. When user interaction is called for in image segmentation, as a consequence of these interpolation methods, the user needs to segment a much greater (typically 4-10x) amount of data. To mitigate this problem, a method called shape-based interpolation of binary data was developed 121. Besides significantly reducing user time, this method has been shown to provide more accurate results than grey-level interpolation. We proposed an approach for the interpolation of grey data of arbitrary dimensionality that generalized the shape-based method from binary to grey data. This method has characteristics similar to those of the binary shape-based method. In particular, we showed preliminary evidence that it produced more accurate results than conventional grey-level interpolation methods. In this paper, concentrating on the three-dimensional (3-D) interpolation problem, we compare statistically the accuracy of eight different methods: nearest-neighbor, linear grey-level, grey-level cubic spline, grey-level modified cubic spline, Goshtasby et al., and three methods from the grey-level shape-based class. A population of patient magnetic resonance and computed tomography images, corresponding to different parts of the human anatomy, coming from different three-dimensional imaging applications, are utilized for comparison. Each slice in these data sets is estimated by each interpolation method and compared to the original slice at the same location using three measures: mean-squared difference, number of sites of disagreement, and largest difference. The methods are statistically compared pairwise based on these measures. The shape-based methods statistically significantly outperformed all other methods in all measures in all applications considered here with a statistical relevance ranging from 10% to 32% (mean = 15%) for mean-squared difference.

Correlation of volumetric magnetization transfer imaging with clinical data in MS

We examined the relations between quantitative volumetric estimates of cerebral lesion load based on magnetization transfer imaging (MTI), clinical data, and measures of neuropsychological function in 44 patients with clinically diagnosed MS. In this population we assessed the correlation between several volumetric MTI measures, measures of neurologic function (Kurtzke Expanded Disability Status Scale and Ambulation Index), and disease duration using Spearman's correlation coefficient. Patients were classified on the basis of neuropsychological test performance as severely impaired, moderately impaired, and normal. We assessed differences between these groups with respect to MTI results using the Kruskal-Wallis test. MTI measures corrected for brain volume were found to correlate with disease duration (p < 0.01) and showed suggestive correlations with measures of neurologic impairment (p < 0.05). Individual neuropsychological tests correlated with MTI measures corrected and not corrected for brain volume (p < 0.001). An MTI measure not corrected for brain volume differed (p < 0.05) between severely impaired, moderately impaired, and normal patients. These preliminary results suggest that volumetric MTI analysis provides new measures that reflect more accurately the global lesion load in the brain of MS patients, and they may serve as a method to study the natural course of the disease and as an outcome measure to evaluate the effect of drugs.

Quantitative assessment of magnetic resonance imaging lesion load in multiple sclerosis

Changes of lesion load on yearly conventional spin echo (CSE) T2-weighted scans of the brain from patients with multiple sclerosis, measured using computer assisted techniques, are used to monitor long term disease evolution, either natural or modified by treatment. Although lesion load measurements have several advantages over clinical measures of outcome (they provide a more objective and sensitive measure of disease evolution, which has a linear distribution and a more strict relation with the underlying pathology), the poor correlation between changes of lesion load and changes of disability is of concern when using such an approach for monitoring multiple sclerosis trials. In this review, the main sources of variation in T2 lesion load from brain MRI of patients with multiple sclerosis will be considered, along with possible strategies to, at least partially, overcome them. Also, some of the newer fully automated techniques to segment multiple sclerosis lesions, which have been validated against manual outlining, and a recently developed coregistration technique are presented. It is hoped that a more reliable and standardised approach to lesion load measurements in multiple sclerosis will lead to better correlation with clinical disease course, to a higher confidence in the results of trials, and to reduced numbers of scans needed to conduct the trials, thus improving cost efficiency and reducing discomfort of the patients.

Isolated U-fiber involvement in MS: preliminary observations

We studied the frequency and location of isolated U-fiber involvement in MS and correlated these findings exploratively with physical disability and neuropsychological impairment. Fifty-three MS patients were examined. Three-millimeter-thick, fast spin-echo T2-weighted MR images and spin-echo postgadolinium T1-weighted images were obtained. Computer software that which had been validated previously for quantitation of MS lesions was used to detect lesions on the T2-weighted images. The Expanded Disability Status Scale (EDSS), Ambulation Index (AI), and a battery of neurocognitive tests were performed on each patient. Forty-two arcuate hyperintensities along the U-fiber were detected by the software in 28 patients (53%). Twenty-seven lesions (64.3%) were seen in the frontal lobe, eight (19.0%) in the temporal lobe, three (7.1%) in the parietal lobe, three (7.1%) in the occipital lobe, and one (2.4%) in both frontal and parietal lobes. Four lesions (9.5%) showed gadolinium enhancement. Seventeen lesions (40%) were hypointense on the T1-weighted images. Scores of three of the 11 neuropsychological tests reflecting performance in executive control and memory were significantly different at least at the p = 0.05 level between the eight patients with multiple, isolated U-fiber lesions and the 45 patients without any or with only a single U-fiber lesion. No significant difference was noted for EDSS or AI. Isolated U-fiber involvement is an underappreciated MR finding in MS. Our preliminary hypothesis is that U-fiber lesions may contribute to neuropsychological impairment, although our observation requires confirmation.

A new in vivo technique for three-dimensional shoulder kinematics analysis

OBJECTIVE

The field of shoulder kinematics research has long relied upon the use of cadaveric models or invasive techniques in human volunteers. In this paper, a novel method is presented that utilizes magnetic resonance imaging (MRI) and a software system called 3DVEWNIX. This method permits non-invasive, repetitive evaluation of living patients for glenohumeral kinematics analysis. The objectives of this study were twofold: to validate the quantitative accuracy of this technique; and to demonstrate glenohumeral relationships in asymptomatic volunteers during internal and external rotation of the arm.

DESIGN

The translational accuracy was first assessed by comparing known cadaveric glenohumeral translations with calculations from MR images of the cadaver. Nine asymptomatic volunteers were subsequently placed in an external shoulder positioning device in the scanner and imaged in 10 degrees increments of actively achieved internal and external rotation. Three-dimensional reconstructions of the glenoid and humerus were used to evaluate the glenohumeral relationships in the tested positions of rotation.

RESULTS

The quantitative analysis revealed an error of 0.61 mm (SEM 0.11 mm). Examination of the volunteers demonstrated normal relationships about the glenohumeral joint in internal and external rotation. In addition, this method provided detailed images of the bony surface architecture from any perspective. These images can be transformed into a cinematic three-dimensional depiction of active shoulder rotation.

CONCLUSION

This new technique offers an accurate, non-invasive method for assessing the normal glenohumeral relationships in shoulder kinematics. We now possess the capability to investigate the kinematics of normal and abnormal shoulder conditions non-invasively in a large patient population.

Comparison of T2 lesion volume and magnetization transfer ratio histogram analysis and of atrophy and measures of lesion burden in patients with multiple sclerosis

PURPOSE

The purpose of this study was twofold: first, to compare two different measures of lesion burden in patients with multiple sclerosis (MS), the magnetization transfer ratio (MTR) histogram and T2 lesion volume; and, second, to investigate the relationship between lesion burden and atrophy in patients with MS.

METHODS

Thirty patients with MS were examined with MR imaging, including fast spin-echo T2- and proton density-weighted sequences as well as magnetization transfer sequences. The lesion burden in each subject was quantitated by MTR histographic analysis and by a computer-based method for calculating the total volume of lesions on T2-weighted images. Additionally, the CSF volume, the brain parenchymal volume, and the percentage of brain parenchymal volume were determined in all patients by using this method and were compared with measurements in eight control subjects.

RESULTS

Significant loss of parenchymal volume was seen in patients with MS as determined by increased CSF volume and decreased percentage of brain parenchymal volume relative to that in age-matched control subjects. An inverse correlation was observed between the peak height of the MTR histogram and T2 lesion volume. T2 lesion volume corresponded positively with CSF volume and inversely with percentage of brain parenchymal volume. The peak height of the MTR histogram corresponded positively with percentage of brain parenchymal volume and inversely with CSF volume.

CONCLUSION

MS patients sustain a significant loss of parenchymal volume (atrophy), which corresponds strongly with increasing lesion burden. T2 lesion volume and peak height of the MTR histogram show good correlation, and the peak height of the MTR histogram shows a superior correlation with measures of brain atrophy as compared with measurements of T2 lesion volume, suggesting that the MTR histogram may be a better indicator of global disease burden than is T2 lesion volume.

Multiple sclerosis lesion quantification using fuzzy-connectedness principles

Multiple sclerosis (MS) is a disease of the white matter. Magnetic resonance imaging (MRI) is proven to be a sensitive method of monitoring the progression of this disease and of its changes due to treatment protocols. Quantification of the severity of the disease through estimation of MS lesion volume via MR imaging is vital for understanding and monitoring the disease and its treatment. This paper presents a novel methodology and a system that can be routinely used for segmenting and estimating the volume of MS lesions via dual-echo fast spin-echo MR imagery. A recently developed concept of fuzzy objects forms the basis of this methodology. An operator indicates a few points in the images by pointing to the white matter, the grey matter, and the cerebro-spinal fluid (CSF). Each of these objects is then detected as a fuzzy connected set. The holes in the union of these objects correspond to potential lesion sites which are utilized to detect each potential lesion as a three-dimensional (3-D) fuzzy connected object. These objects are presented to the operator who indicates acceptance/rejection through the click of a mouse button. The number and volume of accepted lesions is then computed and output. Based on several evaluation studies, we conclude that the methodology is highly reliable and consistent, with a coefficient of variation (due to subjective operator actions) of 0.9% (based on 20 patient studies, three operators, and two trials) for volume and a mean false-negative volume fraction of 1.3%, with a 95% confidence interval of 0%-2.8% (based on ten patient studies).

A Pentium personal computer-based craniofacial three-dimensional imaging and analysis system

Personal computer (PC)-based computing is now ubiquitous in common consumer applications. Although PCs have equaled or surpassed engineering workstations in basic computing power and economy, there is still strong workstation dependency for imaging applications. This article demonstrates that a complete system, based on a Pentium PC (Intel Corporation, Santa Clara, CA) and readily available and inexpensive software, can be built very economically for effective execution of most of the commonly used three-dimensional imaging operations. For the craniofacial application, the Pentium system offers a twofold speed advantage over a Sparc 20 system using similar three-dimensional processing software. The Pentium system allows interactive fuzzy volume rendering, and manipulation and analysis of complex hard and soft-tissue structures.

Global volumetric estimation of disease burden in multiple sclerosis based on magnetization transfer imaging

We report a semiautomated postprocessing method based on magnetization transfer MR imaging that can quantify the extent of global disease in patients with multiple sclerosis. The technique combines segmentation and quantitative analysis of imaging data reflecting the structural integrity of white matter. Applications of this technique may include assessment of disease progress and of the efficacy of experimental therapeutic intervention. The height of the histogram peak corresponding to white matter was found to be lowered in patients with multiple sclerosis and the overall distribution of magnetization transfer ratios was shifted to lower values.

Computer-assisted quantitation of enhancing lesions in multiple sclerosis: correlation with clinical classification

PURPOSE

To study the utility of a computer-assisted method of quantitating enhancing multiple sclerosis (MS) lesions and to correlate this quantitation with the type and duration of disease.

METHODS

Forty untreated patients with MS were studied. The patients had been classified clinically as having either relapsing-remitting (n = 27) or chronic-progressive (n = 13) disease. Postcontrast contiguous 3-mm-thick MR images of the brain were obtained for up to 3 years. The computer program selected potential lesion sites automatically on the basis of the theory of "fuzzy connectedness," which was incorporated into 3DVIEWNIX software. True lesions were selected from these previously detected potential lesions by means of yes/no responses to the program query. The number of enhancing lesions and the enhancing lesions volume were subsequently computed.

RESULTS

The enhancing lesion volume in patients with relapsing-remitting disease was statistically significantly higher than that of patients with chronic-progressive disease. There was a strong positive correlation between the number of enhancing lesions and the enhancing lesion volume. No significant correlation was noted between the change in score on the expanded disability status scale (EDSS) and the change in the number of enhancing lesions, or between the change in EDSS score and the change in enhancing lesion volume. A negative correlation was found between enhancing lesion volume and duration of disease, and between the number of enhancing lesions and duration of disease in the patients who had enhancing lesions.

CONCLUSIONS

Our data suggest that enhancing lesion volume reflects differences in the classification of clinical MS and in the disease activity over time. Computer-assisted quantitation of enhancing lesion volume is a robust, practical, and objective measure of MS activity.

A new computer-assisted method for the quantification of enhancing lesions in multiple sclerosis

PURPOSE

Our goal is to describe a new computerized method for the detection and quantification of enhanced multiple sclerosis (MS) lesions.

METHOD

Gd-DTPA-enhanced, thin section, T1-weighted images of seven patients (involving 336 slice images) with definite MS were analyzed using a new method based on the theory of "fuzzy connected components," developed and implemented on the 3DVIEWNIX software system. Four neuroradiologists selected "true" lesions from the computer-detected potential lesions with a yes/no response to the program query on 2 different days. The enhanced lesion volume and number of enhancing lesions for each image and each observer were subsequently computed. Additional studies involving 720 slices were conducted to determine lesions that were missed by the system.

RESULTS

The intra- and interobserver variability in the system was 0%. It took approximately 1 min of operator time per 3D study. The system output has no false positives and a mean false-negative volume of 1.3%.

CONCLUSION

The novel system calculates enhancing lesion volume and the number of enhancing lesions with very little operator time, inter- and intraoperator variability, or false-positive and false-negative volumes. Computer-based quantification of enhancing lesion volume is an important objective measure of the activity of MS. The system is now in routine use in clinical investigations that study the role of enhancing lesions in the MS disease.

Clinical applications of three-dimensional magnetic resonance image analysis

A methodology for measuring the kinematic parameters of joints in vivo has been refined using the technique of computerized three-dimensional reconstruction from magnetic resonance images. A research protocol has been developed to establish a classification of normal and pathologic foot function that will have broad clinical application. Development of algorithms for a computer-directed program that can predict resultant kinematics and joint morphometry for a given osteotomy or osseous remodeling procedure will assist the surgeon in preoperative surgical planning.

New method of studying joint kinematics from three-dimensional reconstructions of MRI data

A new method of measuring the kinematic parameters of joints has been developed. This article describes the procedure, using tarsal joints as examples. The method uses the technique of computerized three-dimensional reconstruction from magnetic resonance images, taken at regular intervals throughout a foot's range of motion. From these reconstructions, various kinematic information, such as orientation of instantaneous axes, amounts of rotation, amounts and direction of translation, and bony contact areas, is derived. The method is noninvasive and can be applied to individual subjects or patients.